Title: Classification methods for the analysis of LH-PCR data associated with inflammatory bowel disease patients

Authors: Nuttachat Wisittipanit; Huzefa Rangwala; Masoumeh Sikaroodi; Ali Keshavarzian; Ece A. Mutlu; Patrick Gillevet

Addresses: School of Systems Biology, George Mason University, 10900 University Blvd. MSN 5B3, Manassas, Virginia, 20110, USA ' Department of Computer Science, George Mason University, 4400 University Drive, Fairfax, Virginia, 22030, USA ' Microbiome Analysis Centre, Department of Environmental Science and Policy, George Mason University, 4400 University Drive, Fairfax, Virginia, 22030 USA ' Department of Medicine, Section of Gastroenterology, Rush University Medical Centre, Chicago, Illinois, USA ' Department of Medicine, Section of Gastroenterology, Rush University Medical Centre, Chicago, Illinois, USA ' Microbiome Analysis Centre, Department of Environmental Science and Policy, George Mason University, 4400 University Drive, Fairfax, Virginia, 22030 USA

Abstract: The human gut is one of the most densely populated microbial communities in the world. The interaction of microbes with human host cells is responsible for several disease conditions and of criticality to human health. It is imperative to understand the relationships between these microbial communities within the human gut and their roles in disease. In this study we analyse the microbial communities within the human gut and their role in Inflammatory Bowel Disease (IBD). The bacterial communities were interrogated using Length Heterogeneity PCR (LH-PCR) fingerprinting of mucosal and luminal associated microbial communities for a class of healthy and diseases patients.

Keywords: human microbiome; inflammatory bowel disease; IBD; microbial abundance profile; machine learning; support vector machine; SVM; K-nearest neighbour; kNN; classification; length heterogeneity PCR; LH-PCR fingerprinting; polymerase chain reaction; bioinformatics; human gut.

DOI: 10.1504/IJBRA.2015.068087

International Journal of Bioinformatics Research and Applications, 2015 Vol.11 No.2, pp.111 - 129

Accepted: 03 Jul 2013
Published online: 17 Mar 2015 *

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